# The HCP multi-pipeline dataset: an opportunity to investigate analytical variability in fMRI data analysis

arXiv: https://arxiv.org/abs/2312.14493 · HTML: https://mlsanity.com/paper/2312.14493/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Dec 2023.

## Built on by (most cited first, 1 of 1)

- [Mitigating analytical variability in fMRI results with style transfer](https://mlsanity.com/paper/2404.03703/) (2024)

## Abstract (arXiv)

Results of functional Magnetic Resonance Imaging (fMRI) studies can be impacted by many sources of variability including differences due to: the sampling of the participants, differences in acquisition protocols and material but also due to different analytical choices in the processing of the fMRI data. While variability across participants or across acquisition instruments have been extensively studied in the neuroimaging literature the root causes of analytical variability remain an open question. Here, we share the textitHCP multi-pipeline dataset, including the resulting statistic maps for 24 typical fMRI pipelines on 1,080 participants of the HCP-Young Adults dataset. We share both individual and group results - for 1,000 groups of 50 participants - over 5 motor contrasts. We hope that this large dataset covering a wide range of analysis conditions will provide new opportunities to study analytical variability in fMRI.